Category: Design Thinking

Imagine with me: what if novels were written like software. Sometimes it’s useful to approach absurdity and look inside. There might be treasure there. I’ll define software as an executable, a set of instructions, that are interpreted by a machine for some reason. As a data scientist, I think of software as a product, and I think, constantly, of turning data into product. I think of data as inertia and all the code around it as flexible. I worry a lot about the people that use the software (if anybody) and think of them as heterogenous segments. I think of a novel as an executable, a set of instructions, that are interpreted by a human brain for some reason. As[…]

Backcasting is a fantastic technique. It was invented in Canada. You’re welcome to use it. If it sounds like forecasting – well – that’s because it’s kind of like forecasting. With an important difference. That wikipedia page says: Whereas forecasting is predicting the future (unknown) values of the dependent variables based on known values of the independent variable, backcasting can be considered the prediction of the unknown values of the independent variables that might have existed to explain the known values of the dependent variable. I had to re-read it a few times to really get it. Once you get it, it’s just elegant. What’s beautiful is that it can silence the reactive-pure-statistician brain long enough for the prospective centre of the creative brain to imagine several futures. What I like about backcasting[…]

I was 28 and sleepless when I encountered a marketing version of the logistic function. It was beautiful. It’s one of those things you’re taught about in one context, and when you’re shown it from another angle, it expands your mind. It was like discovering Pi for the first time. I could use it to check the assumptions of a market penetration forecast, and substitute my own estimates for others. I felt empowered and delirious from being able to produce a solid forecast. It became a tool as useful as btau or the crosstab. There’s a part of that math, a variable called saturation, that worried me from the outset. Saturation is the maximum percentage of adoption that a market[…]

Bart Gajderowicz delivered a great talk at Machine Intelligence Toronto about how people go through stages in accomplishing a goal [1]. The talk was about homelessness and AI approaches to public policy. I instantly saw a connection to all sorts of tensions that people endure when they set out on a goal. To distill the concept, let’s start off with the idea that people have goals, people have emotions, and that time moves forward. As people make progress towards their goals, their emotions change over time. They start off in a good mood, in a state of uninformed optimism. Then, as negative information overwhelms their ignorance, they enter into a state of informed pessimism. So much negative information builds up[…]

Let’s start with a story. Daan did a traditional fast follow. He calls it Netherflix. His story was: “It’s like Netflix…for The Netherlands!”. At first, he buys rights on the cheap, pays for digital subtitling, and has a successful kickoff. He gets through to 10% household penetration, or roughly 700,000 subscribers, with an annualized gross revenue of about 60 million Euros. The strength of the Euro lets him raid the Anglosphere and he can stock 10,000 hours of content reliably [1]. He gets through the struggle of getting his stack to deliver content and minimize churn. He’s able to host and deliver 10,000 hours reliably, in spite of supporting video players across 11 different front end platforms, and the costs associated with hosting,[…]

Gary Morgenthaler had a few interesting statements to make: “Therefore, when Siri was an independent company, its plan was to map these domains deeply and seamlessly to automate transactions for its users within them. For example, “Buy that Steve Jobs biography book and send it to my dad”; “Send a dozen yellow roses to my wife”; “Book me the usual table for 2 tonight at 8 p.m. at Giovanni’s”; and “Get me 2 box seats for the Giants game on Saturday.” Then comes the question of what solves our biggest problems. Ultimately, Siri’s value is that of automation and removing “friction” on the Internet. Siri achieves this by: (1) understanding speech input in natural language form, (2) mapping user requests[…]

In a game called “Power Grid Factory Manager”, two to five players are challenged with running a factory for five turns. The three sources of randomness (exogenous shocks) are the starting bid order, the increase in the price of energy, and the three starting factory equipments available upon the very first turn. These three sources of randomness are enough to produce all the variety required. No dice here. No reliance on luck. Managers are given the same starting conditions, and have two resources – workers and money. Everybody is paid on the same schedule, where the input costs are subject to random fluctuations and capital must be balanced. There are very large degrees of freedom involved. The person with the[…]

An insight is: New information Executable Causes action Profitable Or, more detailed, an insight is: A piece of information that you didn’t know before, which – Can feasibly executed, culturally acceptable and of a scale relevant to the firm, and – Causes a decision to be made that wouldn’t have been made otherwise, and – Results in profit or a sustainable competitive advantage I’m finally happy with this definition. It aligns with the best innovation rhetoric very nicely and is generalizable to both design thinking and analytics communities.